ArticleFrontiers in plant science2025
Factors influencing net ecosystem carbon change in cold-temperate coniferous forests of the Da Xing'an Mountains: analysis across developmental stages based on stand, structural, and environmental factors.
Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: The Da Xing'an Mountains region harbors China's only cold-temperate coniferous forests and serves as a critical ecological barrier, playing a vital role in forest ecosystems and carbon sequestration. Stand age, shaped by population dynamics, disturbance regimes, and management practices, significantly influences the global carbon cycle. Although forest development is known to correlate with productivity shifts, how production varies across specific stand developmental stages and the relative contributions of driving factors remain poorly understood. Methods: Using data from the National Forest Continuous Inventory (NFCI, 2005-2010) in the eastern Da Xing'an Mountains, we analyzed the effects of stand characteristics, structural diversity, and environmental variables on Net Ecosystem Carbon Change (NECC) across a spectrum of developmental stages, from young to overaged forests. Results: Our findings demonstrate that: (1) Net Ecosystem Carbon Change (NECC) is co-limited by stand characteristics, structural diversity, and environmental factors, with stand characteristics exerting the strongest influence, primarily via direct effects. (2) As stands develop, the impacts of structural diversity (effect increasing from 8.68% to 16.44%) and soil factors (from 8.80% to 10.30%) on productivity intensify. (3) In contrast, the influence of climate (decreasing from 30.40% to 17.67%) and terrain (from 14.55% to 6.28%) diminishes with advancing growth stages. Discussion: This study provides a comprehensive, system-level analysis of the determinants of Net Ecosystem Carbon Change (NECC). By integrating multiple drivers, our work establishes a theoretical foundation for predicting Net Ecosystem Carbon Change (NECC) changes under global change scenarios. These insights are crucial for formulating effective forest management strategies to mitigate the challenges of climate change and biodiversity loss.
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